NDLI: Color Face Detection Using Unit-Linking Pulse Coupled Neural Network

Content Provider	IEEE Xplore Digital Library
Author	Haiyan Li Dan Xu Rong Zong Zhengyao Bai
Copyright Year	2008
Description	Author affiliation: Coll. of Inf. Sci. & Technol., Yunnan Univ., Kunming (Haiyan Li; Dan Xu; Rong Zong; Zhengyao Bai)
Abstract	In this paper, a novel method is proposed to detect faces based on PCNN time signature and skin color segmentation, in which no training is needed. A test image is first divided into overlapped blocks and extracted PCNN time signature as the detection features, which a two-dimensional image is projected to a one-dimensional feature space. The test blocks are matched to a face template, which can be a random face, not related to the test faces, based on Euclidean distance threshold. The candidate face blocks are clustered to determine the face number included in a probe image and the size of the face areas. Skin color segmentation is used to reduce the search areas and to speed up the detection procedure. The method demonstrates successful face detection over a wide range of facial variations in scale, resolution, facial expressions, with or without glasses, in the presence of various illumination conditions as well as under complex background from outdoor photo collections. The simulation result proves that the method is translation, rotation and scale invariant as well as insensitive to illumination changes.
Starting Page	466
Ending Page	470
File Size	600214
Page Count	5
File Format	PDF
ISBN	9780769534909
DOI	10.1109/PACIIA.2008.252
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-19
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer vision PCNN time signature face detection unit-linking PCNN Glass Face detection Image segmentation Neural networks Lighting PCNN Euclidean distance Skin Probes Testing skin color segmentation
Content Type	Text
Resource Type	Article

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